Arrangement for, and method of, analyzing wireless local area network (WLAN) field coverage in a venue

ABSTRACT

Wireless local area network (WLAN) field coverage is analyzed in a venue. A mobile data capture device measures coverage data indicative of the WLAN field coverage from a plurality of locations in the venue, and also captures image data indicative of images of the locations in the venue. A controller correlates the measured coverage data and the captured image data at each location. An interface displays the captured image data correlated with the measured coverage data at each location. Impact score value data indicative of the WLAN field coverage may also be determined, correlated, and displayed for each location.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is related to, and claims the benefit under 35U.S.C. § 119(e) of, U.S. Provisional Patent Application No. 62/309,659,filed Mar. 17, 2016, and entitled “Capturing, Visualization, andAnalysis of WLAN field coverage.” The present application is acontinuation of U.S. patent application Ser. No. 15/293,026, filed Oct.13, 2016, and entitled “Arrangement For, and Method of, AnalyzingWireless Local Area Network (WLAN) Field Coverage in a Venue.” Theentire contents of said applications being incorporated in the instantapplication by this reference thereto.

BACKGROUND OF THE INVENTION

The present disclosure generally relates to an arrangement for, and amethod of, analyzing wireless local area network (WLAN) field coveragein a venue, either indoors or outdoors.

For product locationing, product tracking, product identification, andinventory control of products in a retail, factory, or warehouseenvironment, or a like indoor or outdoor venue, it is known towirelessly link one or more mobile data capture devices in a wirelesslocal area network (WLAN) having a plurality of base stations (e.g.,access points) deployed in the venue under the control of a networkcomputer or host server. For example, one type of mobile data capturedevice may be a radio frequency (RF) identification (RFID) tag readerfor reading RFID tags, and/or a near field communication (NFC) tagreader for reading NFC tags, the tags being associated with the productsin the venue, and another type of mobile data capture device may beeither a laser-based or an imager-based bar code symbol reader forreading bar code symbols associated with the products in the venue. Thebase stations propagate a WLAN field in the venue by transmitting andreceiving RF signals to and from such mobile devices to enable the usersof the mobile devices to move freely within the venue and still beconnected to the WLAN, and, if desired, to the wider Internet. Manymodern WLANs are advantageously based on the Institute of Electrical andElectronics Engineers (IEEE) 802.11 standards, marketed under theWireless Fidelity (Wi-Fi) brand name.

It is often important to analyze or map the coverage of the WLAN fieldof the RF signals propagated by the base stations in the venue, bothprior to establishing the WLAN during network planning, and afterestablishing the WLAN during monitoring/debugging. Strong RF signalcoverage is typically found in certain so-called “hot” zones in thevenue, typically in the immediate vicinity of each base station.However, some RF signals may be reflected and/or scattered alongmultiple, folded paths, and/or at least partially absorbed, by walls,ceilings, floors, shelving structures, and like permanent fixtures andobstructions. In addition, some RF signals may, from time to time, beunpredictably and temporarily attenuated by people walking through thevenue, or by forklifts driving through the venue, or by doors beingclosed, or by some transitory movement of another object or person. Suchmulti-path propagation and transitory environmental conditions may causeweak, poor, or even no WLAN field coverage in certain so-called “cold”zones in the venue and may compromise network communications and datacapture performance. Additional base stations or other network hardware,or additional software, may need to be deployed and configured toprovide more uniform and adequate WLAN field coverage in the venue,especially in the cold zones, thereby burdening customer supportpersonnel and resources.

It is known to perform a site survey to analyze the WLAN field coveragein a venue by sampling the RF signals propagated by the base stations.Although generally satisfactory for its intended purpose, the survey ormapped data produced by such sampling is only valid for the time, andonly for the specific physical obstructions and/or environmentalconditions, during which the survey was conducted. A network analystreviewing the survey data will not know, for example, whether aparticular cold zone was caused by poor deployment of the base stations,or by the presence of some permanent fixture or obstruction, or by sometemporary environmental condition such as the transitory movement ofsome object or person, among other factors. Once the survey iscompleted, the analyst may not readily be able to resurrect the physicalobstructions and/or environmental conditions during which the survey wasconducted. This may lead to an incorrect WLAN field coverage analysis.For example, a particular temporary obstruction and/or environmentalcondition may not recur, and a zone deemed cold at one time may actuallybe hot at another time.

Accordingly, it would be desirable to render the WLAN field coverageanalysis more accurate for network planning/monitoring/debuggingpurposes, to reduce the burden on customer support personnel andresources, and to readily enable an analyst to resurrect the physicalobstructions and/or environmental conditions in which a site survey wasconducted.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The accompanying figures, where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, together with the detailed description below, are incorporated inand form part of the specification, and serve to further illustrateembodiments of concepts that include the claimed invention, and explainvarious principles and advantages of those embodiments.

FIG. 1 is a top plan view of a warehouse environment or venue havingproducts associated with data to be captured by mobile data capturedevices that are linked in a WLAN having multiple base stations forpropagating a WLAN field in an arrangement for analyzing the coverage ofthe WLAN field in accordance with the present disclosure.

FIG. 2 is a diagrammatic view depicting a representative user, and arepresentative automated vehicle, each operative for moving mobile datacapture devices in the venue of FIG. 1.

FIG. 3 is a block diagram of some of the components of the arrangementof FIG. 1.

FIG. 4A and FIG. 4B together comprise a screen shot on a display screenof image data captured by each mobile data capture device, WLAN fieldcoverage data measured by each mobile data capture device and correlatedwith the image data, as well as impact score value data correlated withthe image data and the WLAN field coverage data.

FIG. 5 is a table of representative physical obstructions and patternsindexes for use in determining the impact score value data for displayon the display screen of FIGS. 4A and 4B.

FIG. 6 is a table of representative environmental conditions indexesalso used in determining the impact score value data for display on thedisplay screen of FIGS. 4A and 4B.

FIG. 7 is a flow chart of steps performed in determining the impactscore value data for display on the display screen of FIGS. 4A and 4B.

FIG. 8 is a flow chart of a method of analyzing the WLAN field coveragein accordance with the present disclosure.

Skilled artisans will appreciate that elements in the figures areillustrated for simplicity and clarity and have not necessarily beendrawn to scale. For example, the dimensions and locations of some of theelements in the figures may be exaggerated relative to other elements tohelp to improve understanding of embodiments of the present invention.

The arrangement and method components have been represented whereappropriate by conventional symbols in the drawings, showing only thosespecific details that are pertinent to understanding the embodiments ofthe present invention so as not to obscure the disclosure with detailsthat will be readily apparent to those of ordinary skill in the arthaving the benefit of the description herein.

DETAILED DESCRIPTION OF THE INVENTION

One aspect of this disclosure relates to an arrangement for analyzingcoverage of a wireless local area network (WLAN) field in a venue. Thearrangement includes a mobile data capture device movable in the venue,for example, by a walking human operator, or by an automated vehicle,such as a land or aerial vehicle. Advantageously, a plurality of basestations, e.g., access points, propagates the WLAN field in the venue bytransmitting and receiving radio frequency (RF) signals to and from themobile data capture device. The mobile data capture device measurescoverage data indicative of the WLAN field coverage from a plurality oflocations in the venue, and captures image data indicative of images ofthe locations in the venue. A controller, for example, a programmedmicroprocessor, is operatively connected to the mobile data capturedevice, and correlates the measured coverage data and the captured imagedata at each location. Advantageously, impact score value data, which isindicative of physical obstructions and/or environmental conditions inthe venue, may also be determined and correlated with the measuredcoverage data and the captured image data at each location. An interfaceis operatively connected to the controller, and displays the capturedimage data correlated with the measured coverage data at each location.The correlated impact score value data may also be displayed on theinterface.

In a preferred embodiment, the mobile data capture device may have an RFreceiver for receiving the propagated RF signals indicative of the WLANfield coverage, and the controller measures the coverage data bysampling strengths of the received RF signals. The RF receiver is alsooperative for receiving a plurality of the propagated RF signalstransmitted from RF transmitters at fixed, known positions in the venue,in which case the controller locates the mobile data capture device ateach location by measuring strengths of the plurality of the received RFsignals, e.g., by triangulation, trilateration, or like techniques.Advantageously, the mobile data capture device has a camera, or likeimager, for capturing the image data over an imaging field of view, anda movable mount is preferably provided for moving the camera and theimaging field of view. Advantageously, the mount enables the camera tobe rotated and/or tilted to desired extents.

The interface preferably includes a display screen, and the controllercontrols the display screen to simultaneously display the captured imagedata and the measured coverage data, and, optionally, the impact scorevalue data, that are correlated at each location that is selected by ananalyst who is analyzing the WLAN field coverage. The simultaneousdisplay of the captured image data and the measured coverage data, aswell as the optional impact score value data, is advantageouslyperformed in real time as the mobile data capture device moves throughthe venue. Alternatively or in addition, the simultaneous display of thecaptured image data and the measured coverage data, as well as theoptional impact score value data, at respective locations may beperformed after the corresponding measurements have been taken andrecorded by the mobile data capture device. As those of skill in the artwill realize, the foregoing simultaneous display may take place on themobile data capture device itself and/or on another computing devicebased on either real-time or recorded data.

A further aspect of this disclosure is directed to a method of analyzingwireless local area network (WLAN) field coverage in a venue. The methodis performed by moving a mobile data capture device in the venue, bymeasuring coverage data indicative of the WLAN field coverage from aplurality of locations in the venue, by capturing image data indicativeof images of the locations in the venue, by correlating the measuredcoverage data and the captured image data at each location, and bydisplaying the captured image data correlated with the measured coveragedata at each location. The aforementioned impact score value data mayalso be determined, correlated, and displayed for each location.

In accordance with this disclosure, the display of the captured imagedata correlated with the measured coverage data at each location, and,optionally, the correlated impact score value data, enables an analystor user to resurrect the physical obstructions and/or environmentalconditions under which the WLAN field coverage analysis was conducted.Thus, the analyst can view the captured image data and determine, amongother things, whether a particular cold zone was caused by a poorplacement of the base stations, or by a permanent fixture orobstruction, or by some transitory movement by a person or object, or bysome environmental condition, or by some other factor. The WLAN fieldcoverage analysis is therefore performed more accurately thanheretofore.

Turning now to the drawings, reference numeral 10 in FIG. 1 generallydepicts a warehouse environment or venue in which products 12, shown inFIG. 1 as boxes or cartons for simplicity, are associated with inventorydata to be captured by mobile data capture devices 22, as describedbelow. The venue 10 may be any indoor or outdoor venue, and may have anylayout or configuration. As shown in FIG. 2, a zone of the venue 10 mayhave, for example, a plurality of shelving structures 6 and 8 separatedby an aisle 4, and the products 12 can be mounted on the shelvingstructures 6, 8. Each product 12 may be tagged with a radio frequency(RF) identification (RFID) tag, preferably a passive RFID tag for costreasons, and/or with a near field communication (NFC) tag, and, in someapplications, each RFID/NFC tag may be associated with a pallet, or acontainer, for supporting multiple products 12. Each product 12 may,additionally or alternately, advantageously be labeled with a bar codesymbol, or with any other type of identifier.

As shown in FIG. 3, each mobile capture device 22 has a data capturemodule 26 operative, for example, as an RFID and/or NFC tag reader forreading the RFID and/or NFC tags that are associated with the products12, or as a laser-based or an imager-based bar code symbol reader forreading the bar code symbols associated with the products 12. Such datacapture identifies the products for such purposes as locationing,tracking, and inventory control. Each mobile capture device 22 may alsobe provided with a voice communication module. As shown in FIGS. 1-2,the mobile capture device 22 may be configured to be handheld andcarried by a human operator 24 as the operator walks through the venue10, or the mobile capture device 22 may be supported by an automatedvehicle 28 during travel through the venue. As shown, the vehicle 28 isa land cart having wheels 32 and is self-propelled, for example, eitherautonomously, or by the operator, or by remote control, along the aisle4 between the shelving structures 6, 8 past the products 12 in thedirection of the arrow “A”. The vehicle 28 may be any form ofconveyance, either human-propelled or motor-propelled, and, for example,may even be an aerial vehicle or flying drone. In one embodiment, thevehicle 28 is a robotic vehicle configured for data collection andautonomous navigation throughout the venue 10.

As also shown in FIGS. 1-2, the mobile data capture devices 22 arewirelessly linked together in a wireless local area network (WLAN)having a plurality of base stations (e.g., access points) 20 deployed inthe venue under the control of a network computer or host server 16. Inan embodiment, the base stations 20 can, for example, be installed everytwenty to eighty feet or so apart in a grid pattern. The base stations20 propagate a WLAN field in the venue 10 by transmitting and receivingradio frequency (RF) signals to and from the mobile devices 22 to enablethe operators 24 and/or the vehicles 28 to move freely within the venue10 and still be connected to the WLAN, and, if desired, to the widerInternet. An advantageous embodiment of the WLAN may be based on theInstitute of Electrical and Electronics Engineers (IEEE) 802.11standards, marketed under the Wireless Fidelity (Wi-Fi) brand name. Thehost server 16 is typically locally located in a backroom at the venue10, and comprises one or more computers and is in communication witheach base station 20. The server 16 may also be remotely hosted in acloud server. The server 16 controls each base station 20. In oneembodiment, the server 16 also controls an interface 14, as describedbelow.

In accordance with this disclosure, the coverage of the WLAN field inwhich the RF signals are propagated in the venue 10 is to be mapped andanalyzed as a result of the mobile device 22 moving through a pluralityof locations in the venue 10. As shown in FIGS. 2-3, the mobile device22 may be located by transmitting a plurality of RF signals from acorresponding plurality of transmitters 34 provided in a correspondingplurality of the base stations 20 along RF signal paths 18 to a receiver30 provided in the mobile device 22. The positions of the base stations20 are fixed and known. A device controller 36 in the mobile device 22measures the strength of the received RF signals, and the distancebetween the mobile device 22 and each base station 20 is determined bytriangulation, trilateration, or like locating techniques known in theart.

Many other types of locating techniques can be used for locating themobile device 22 inside the venue 10. For example, an ultrasoniclocationing system may be employed for locating the mobile device 22 bytransmitting an ultrasonic signal to an ultrasonic receiver, e.g., amicrophone 38, on the mobile device 22. More particularly, a pluralityof ultrasonic transmitters, such as voice coil or piezoelectricspeakers, mounted, for example, at known, fixed positions in the venue,can transmit ultrasonic energy to the microphone 38. The receipt of theultrasonic energy at the microphone 38 locates the mobile device 22.Each ultrasonic speaker periodically transmits ultrasonic rangingsignals, preferably in short bursts or ultrasonic pulses, which arereceived by the microphone 38 on the mobile device 22. The microphone 38determines when the ultrasonic ranging signals are received. The flighttime difference between the transmit time that each ranging signal istransmitted and the receive time that each ranging signal is received,together with the known speed of each ranging signal, as well as theknown and fixed locations and positions of the speakers, are all used todetermine the position of the microphone 38 and of the mobile device 22,using a suitable locationing technique, such as triangulation,trilateration, multilateration, among others.

The RF receiver 30 can also receive RF signals indicative of the WLANfield coverage. The device controller 36 samples the strengths of thereceived RF signals, and thereby measures coverage data indicative ofthe WLAN field coverage from the locations in the venue. In addition, acamera 40 is provided in the mobile device 22 and is operated by thedevice controller 36 to capture image data indicative of images of thelocations in the venue 10 over an imaging field of view (FOV), as wellas to capture the times that the image data were taken. The FOV is thesolid angle over which the camera 40 is sensitive to light returningfrom the locations in the venue 10. The device controller 36 thencorrelates the measured coverage data and the captured time-stampedimage data at each location in the venue 10. As described below inconnection with FIGS. 4A and 4B, the interface 14 displays the capturedtime-stamped image data correlated with the measured coverage data ateach location.

More particularly, as shown in FIG. 3, the server 16 includes a servercontroller 42 and a server memory 44. The interface 14 includes adisplay monitor screen 46 and a keyboard 48 or analogous manual entrydevice. The server controller 42 controls the interface 14 and adatabase 50. The mobile device 22 also includes a device memory 52, abattery 54 for powering the mobile device 22, and, preferably, anaccelerometer 56 for determining the position and/or orientation of themobile device 22. The measured coverage data and the capturedtime-stamped image data may be recorded and stored in the device memory52 and/or in the server memory 44 and/or in the database 50. Themeasured coverage data and the captured time-stamped image data may becorrelated by the device controller 36 and/or by the server controller42. In an embodiment, the camera 40 includes a wide-angle lens in orderto capture a wide field of view (FOV) within the WLAN field coveragefield at each location of the mobile device 22. Alternatively or inaddition, the camera 40 is a panoramic camera configured for capturingpanoramic image data at a plurality of locations of the mobile device22.

In one mode of operation, as the operator 24 walks through the venue 10,he/she may aim the field of view of the camera 40 in any direction, andfor as long as desired, and the camera 40 captures time-stamped imagesof the locations or scenes in the venue, while the receiver 30 issubstantially simultaneously measuring the WLAN field at theselocations. In another mode of operation, the vehicle 28 advances throughthe venue, and the camera 40 of the supported mobile device 22 isoperated to capture time-stamped images of the locations or scenes inthe venue, while the receiver 30 of the supported mobile device 22 issubstantially simultaneously measuring the WLAN field at theselocations. The supported mobile device 22 is advantageously mounted on astage or platform 58 (see FIG. 2), which can rotate the supported mobiledevice 22 in azimuth in either circumferential direction, as indicatedby arrow “B”, about a vertical axis, and/or tilt the supported mobiledevice 22 up or down in elevation to thereby aim the field of view inany desired direction and for as long as desired. The accelerometer 56assists in determining the position and orientation of the supportedmobile device 22. The vehicle 28 can advantageously be programmed to runon a predetermined automatic schedule, for example, at night, and alonga predetermined route.

FIGS. 4A and 4B together comprise a representative screen shot that isdisplayed on the display 46 of the interface 14, and includes, amongother things, the simultaneous display of the captured image data 60 andthe measured coverage data 62. Alternatively or in addition, the screenshot of FIGS. 4A and 4B may be displayed directly on an onboard displayof the mobile device 22. The measured coverage data 62 is a graphicalrepresentation of received signal strength intensity (RSSI), expressedin −dBm units, of RF signals propagated from the multiple base stations20 along the Y-axis, and of time along the X-axis. In an embodiment, thegraphs can be drawn in real time as the mobile device 22 is moved. Theimage data 60 and the coverage data 62 can be viewed in real time, orthey can be recorded and stored, e.g., in the database 50, forsubsequent viewing and analysis. The image data 60 is an actualdepiction or picture, such as a photo or a video frame, of the physicalscene at each location and corresponding time, e.g., at the timeselected by a line or cursor 64. The layout of the image data 60 and thecoverage data 62 can be in portrait or landscape orientation, with thepositions of the image data 60 and the coverage data 62 being reversedand/or at least partly overlaid, and with the sizes of the image data 60and the coverage data 62 being varied or fixed. For example, in oneembodiment, the image data 60 corresponding to a time instance selectedby the line or cursor 64 (FIG. 4B) may be shown in an embedded imagedata window at the top of the line or cursor 64, wherein the embeddedimage data window is updated as a user slides the line or cursor 64along the graph representing the time-varying coverage data 62.

Impact score value data 66, which typically is a numerical valueindicative of physical obstructions, such as those listed in the tableof FIG. 5, and/or environmental conditions, such as those listed in thetable of FIG. 6, in the venue 10, may also be simultaneously displayedand updated on the display 46, or on the onboard display of the mobiledevice 22, and correlated with the respective captured image data 60 andthe respective measured coverage data 62. In order to determine theimpact score value data 66, the device controller 36 is also operative,as described below, for recognizing such predetermined obstructionsand/or environmental conditions from the captured image data. Forexample, a visual recognition algorithm, such as represented by the flowchart of FIG. 7, can be programmed on the device controller 36 torecognize such obstructions and/or environmental conditions, and todetermine and display the impact score value data 66 for each suchrecognized obstruction and/or condition.

Thus, as shown in FIG. 5, a plurality of representative predeterminedobstructions, patterns, or objects of various material types and statesare indexed by numerals 1 . . . N and stored in a database accessible bythe device controller 36 as a table of obstructions and pattern indexes(OPI). Each such obstruction/pattern is associated with an OPIcoefficient (OPIC), which is a default numerical value that isapproximately indicative of the extent to which it obstructs, e.g.,attenuates, the WLAN field. Thus, a greater OPIC, such as 5 associatedwith an empty metal shelf (index 5) attenuates the WLAN field more thana dry wall (index 3) whose OPIC is 1. The default OPICs form part of apre-established propagation model.

Each such obstruction/pattern listed in the table of FIG. 5 is alsoassociated with a weighting factor relating to the distance OPIC-Dbetween the respective obstruction/pattern and the mobile device. Thedistance can be determined by a rangefinder, or preferably from thecaptured image data in combination with data indicating a correspondingfocal length of the focusing lens system of the camera 40. Eachweighting factor is inversely proportional to the distance. Thus, thegreater the distance, the lesser the WLAN field is attenuated by therespective obstruction/pattern. As illustrated, indexes 1-6 arereciprocals of the distance raised to the first power, whereas indexes7-11 are reciprocals of the distance raised to higher powers, therebysignifying the different extents at which the attenuation changes withdistance for indexes 1-6 as compared to indexes 7-11. As further shownin FIG. 5, indexes 7-11 are associated with possible RF emission, whichmay result in signal interference. In one embodiment, an indicator of apossible RF emission/interference source is provided for the user, forexample, by visually tagging a respective object detected in the imagedata and displayed at the interface 14 and/or the mobile device 22.

Turning now to FIG. 6, a plurality of predetermined environmentalconditions are indexed by numerals 1 . . . N and stored in a databaseaccessible by the device controller 36 as a table of environmentalconditions indexes (ECI). Each such environmental condition isassociated with a determination (yes or no) whether or not a basestation 20 is or is not detected, respectively, in the image data 60.Each environmental condition is also associated with an ECI penalizefactor (ECI-PF), which is a default numerical multiplier value that isapproximately indicative of the extent to which the respectiveenvironmental condition attenuates the WLAN field. Thus, a greaterECI-PF, such as 2 associated with an inside small room in which a basestation has not been detected (index 3) attenuates the WLAN field morethan an inside small room in which a base station has been detected(index 2) whose ECI-PF is 1. The default ECI-PFs also form part of thepre-established propagation model.

The flow chart of FIG. 7 depicts the steps performed by the devicecontroller 36 to recognize the obstructions of FIG. 5 and/or theenvironmental conditions of FIG. 6, and to determine and display theimpact score value data 66 for each such recognized obstruction and/orcondition at each location in the venue 10. First, the camera 40 detectsthe OPI and/or the ECI from the captured image data in step 70. Then,the device controller 36 fetches and retrieves the stored OPIC from theassociated detected OPI from the database in step 72. In step 74, thedevice controller 36 calculates the distance between the associateddetected OPI and the mobile device 22, and the device controller 36fetches and retrieves the stored OPIC-D from the database. In step 76,the device controller 36 calculates a first approximation(Approximation1) of the impact score value data by multiplying OPIC byOPIC-D. Although the steps 70, 72, 74 and 76 have been individuallyillustrated in FIG. 7 for purposes of clarity, they can all be performedin a single step. The device controller 36 fetches and retrieves thestored ECI-PF from the database in step 78. In step 80, the devicecontroller 36 calculates a second approximation (Approximation2) of theimpact score value data 66 by multiplying Approximation1 by ECI-PF.Although the steps 78 and 80 have been individually illustrated in FIG.7 for purposes of clarity, they can both be performed in a single step.

Next, in step 82, the device controller 36 determines whether a map ofthe venue 10 has been preloaded on the mobile device 22. If not, thenthe impact score value data 66 is considered to be Approximation2, andthis impact score value data 66 is relayed to the device controller 36for further processing and/or for display in step 84. If the map waspreloaded, then the device controller 36 locates the mobile device 22 onthe map in step 86, and then determines whether or not the OPI and/orthe ECI can also be found on the map in step 88. If not, then the impactscore value data 66 is again considered to be Approximation2, and thisimpact score value data 66 is relayed to the device controller 36 forfurther processing and/or for display in step 84. However, if the OPIand/or the ECI can be found on the map, then the device controller 36refines and updates the OPIC, OPIC-D and the ECI-PF values based onadditional information or metadata provided by the map in step 90, andcalculates, in step 92, a first refined recalculation (Refined1) of theimpact score value data 66 by multiplying the refined OPIC by therefined OPIC-D, and by calculating a second refined recalculation(Refined2) of the impact score value data 66 by multiplying Refined1 bythe refined ECI-PF. The impact score value data 66 is now considered tobe Refined2, and this impact score value data 66 is relayed to thedevice controller 36 for further processing and/or for display in step84.

An analyst or user that is viewing the screen shot of FIGS. 4A and 4Bmay move the cursor 64 to any desired time along the X-axis to view thecorresponding actual image of the mobile device location and,optionally, the impact score value data 66, at that time. For example,the analyst may see that a particular location has a low RSSI, or a highimpact score value data 66, that is indicative of a cold zone of poorcoverage, and may wish to see the actual environmental conditions atthat location and time to try and determine why the coverage of thatzone was poor. The analyst might see nothing unusual, or might see somephysical obstruction or environmental condition for such poor coverage,and recommend corrective action. Non-limiting examples of correctiveaction may include re-measuring field coverage when the physicalobstruction is removed, moving base station locations, adjusting thepower output of the base stations to take into account the existence andattenuation characteristics of identified obstructions (e.g., metallicobstructions, non-metallic obstructions, temporary shelving), amongothers. In accordance with this disclosure, the analyst can resurrectthe physical or environmental conditions in which the WLAN fieldcoverage measurement was conducted and perform a more accurate WLANanalysis than heretofore.

In yet another embodiment, the characteristics of the RF propagationenvironment identified from the captured image data, includingattenuation constants corresponding to obstructions, wall types, orother environmental condition variables affecting coverage in the venue10, are provided to an RF propagation modeling computer for enhancingthe accuracy of modeling various coverage scenarios within the venue(e.g., modeling predicted coverage effects based on changing position,antenna types, and/or power output of one or more of the base stations20).

The flow chart of FIG. 8 depicts the operation of the method of thisdisclosure. The method of analyzing WLAN field coverage is performed bymoving a mobile data capture device 22 in the venue 10 in step 100, bylocating the mobile device 22 in the venue 10 in step 102, by measuringcoverage data indicative of the WLAN field coverage at each location instep 104, by capturing image data indicative of images of each locationin step 106, by correlating the measured coverage data and the capturedimage data at each location in step 108, and by displaying the capturedimage data correlated with the measured coverage data at each locationin step 110. The aforementioned impact score value data 66 may also bedetermined, correlated, and displayed for each location in step 112.

In the foregoing specification, specific embodiments have beendescribed. However, one of ordinary skill in the art appreciates thatvarious modifications and changes can be made without departing from thescope of the invention as set forth in the claims below. Accordingly,the specification and figures are to be regarded in an illustrativerather than a restrictive sense, and all such modifications are intendedto be included within the scope of present teachings.

The benefits, advantages, solutions to problems, and any element(s) thatmay cause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as a critical, required, or essentialfeatures or elements of any or all the claims. The invention is definedsolely by the appended claims including any amendments made during thependency of this application and all equivalents of those claims asissued.

Moreover in this document, relational terms such as first and second,top and bottom, and the like may be used solely to distinguish oneentity or action from another entity or action without necessarilyrequiring or implying any actual such relationship or order between suchentities or actions. The terms “comprises,” “comprising,” “has,”“having,” “includes,” “including,” “contains,” “containing,” or anyother variation thereof, are intended to cover a non-exclusiveinclusion, such that a process, method, article, or apparatus thatcomprises, has, includes, contains a list of elements does not includeonly those elements, but may include other elements not expressly listedor inherent to such process, method, article, or apparatus. An elementproceeded by “comprises . . . a,” “has . . . a,” “includes . . . a,” or“contains . . . a,” does not, without more constraints, preclude theexistence of additional identical elements in the process, method,article, or apparatus that comprises, has, includes, or contains theelement. The terms “a” and “an” are defined as one or more unlessexplicitly stated otherwise herein. The terms “substantially,”“essentially,” “approximately,” “about,” or any other version thereof,are defined as being close to as understood by one of ordinary skill inthe art, and in one non-limiting embodiment the term is defined to bewithin 10%, in another embodiment within 5%, in another embodimentwithin 1%, and in another embodiment within 0.5%. The term “coupled” asused herein is defined as connected, although not necessarily directlyand not necessarily mechanically. A reader or structure that is“configured” in a certain way is configured in at least that way, butmay also be configured in ways that are not listed.

It will be appreciated that some embodiments may be comprised of one ormore generic or specialized processors (or “processing readers”) such asmicroprocessors, digital signal processors, customized processors, andfield programmable gate arrays (FPGAs), and unique stored programinstructions (including both software and firmware) that control the oneor more processors to implement, in conjunction with certainnon-processor circuits, some, most, or all of the functions of themethod and/or apparatus described herein. Alternatively, some or allfunctions could be implemented by a state machine that has no storedprogram instructions, or in one or more application specific integratedcircuits (ASICs), in which each function or some combinations of certainof the functions are implemented as custom logic. Of course, acombination of the two approaches could be used.

Moreover, an embodiment can be implemented as a computer-readablestorage medium having computer readable code stored thereon forprogramming a computer (e.g., comprising a processor) to perform amethod as described and claimed herein. Examples of suchcomputer-readable storage mediums include, but are not limited to, ahard disk, a CD-ROM, an optical storage reader, a magnetic storagereader, a ROM (Read Only Memory), a PROM (Programmable Read OnlyMemory), an EPROM (Erasable Programmable Read Only Memory), an EEPROM(Electrically Erasable Programmable Read Only Memory) and a Flashmemory. Further, it is expected that one of ordinary skill,notwithstanding possibly significant effort and many design choicesmotivated by, for example, available time, current technology, andeconomic considerations, when guided by the concepts and principlesdisclosed herein, will be readily capable of generating such softwareinstructions and programs and ICs with minimal experimentation.

The Abstract of the Disclosure is provided to allow the reader toquickly ascertain the nature of the technical disclosure. It issubmitted with the understanding that it will not be used to interpretor limit the scope or meaning of the claims. In addition, in theforegoing Detailed Description, it can be seen that various features aregrouped together in various embodiments for the purpose of streamliningthe disclosure. This method of disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter lies in less than allfeatures of a single disclosed embodiment. Thus, the following claimsare hereby incorporated into the Detailed Description, with each claimstanding on its own as a separately claimed subject matter.

The invention claimed is:
 1. A system for analyzing wireless local areanetwork (WLAN) field coverage in a venue, the system comprising: amobile data capture device movable in the venue, and operative to:measure coverage data indicative of the WLAN field coverage from aplurality of locations in the venue, and capture image data indicativeof images of the locations in the venue; a controller operativelyconnected to the mobile data capture device, the controller correlatingthe measured coverage data and the captured image data at each location;and an interface operatively connected to the controller, the interfacedisplaying the captured image data correlated with the measured coveragedata at each location, wherein the controller recognizes a type of venuefrom the captured image data as one of an open venue or an enclosedvenue, determines a coverage impact score value data based on therecognized type of venue from the captured image data by referencing alookup table from memory to determine the coverage impact score valuedata corresponding to the type of venue recognized from the capturedimage data and stored in the table, correlates the determined coverageimpact score value data with the captured image data and with themeasured coverage data, and causes the interface to display thecorrelated coverage impact score value data with the captured image dataand with the measured coverage data at each location.
 2. The system ofclaim 1, wherein the mobile data capture device receives a plurality ofradio frequency (RF) signals from RF transmitters at fixed, knownpositions in the venue, and wherein the controller locates the mobiledata capture device at each location by measuring strengths of theplurality of the received RF signals.
 3. The system of claim 1, furthercomprising a database accessible by the controller, and wherein thecontroller records and stores the correlated coverage data and the imagedata at each location in the database.
 4. The system of claim 1, whereinthe interface has a display screen, and wherein the controller controlsthe display screen to simultaneously display the captured image data andthe measured coverage data at each location selected by a user.
 5. Thesystem of claim 1, wherein the controller controls a display screen tosimultaneously display the captured image data and the measured coveragedata in real time as the mobile data capture device moves through thevenue.
 6. The system of claim 1, wherein the controller locates at leastone recognized object on a map, updates a default value assigned to theat least one recognized object to a refined value, and determines thecoverage impact score value data based on the refined value.
 7. A methodof analyzing wireless local area network (WLAN) field coverage in avenue, the method comprising: measuring, by a mobile data capturedevice, coverage data indicative of the WLAN field coverage from aplurality of locations in the venue; capturing, by the mobile datacapture device, image data indicative of images of the locations in thevenue; recognizing, by a controller operatively connected to the mobiledata capture device, a type of venue from the captured image data as oneof an open venue or an enclosed venue; determining, by the controller, acoverage impact score value data based on the type of venue byreferencing a lookup table from memory to determine the coverage impactscore value data corresponding to the type of venue recognized from thecaptured image data and stored in the table; correlating, by thecontroller, the determined coverage impact score value data with thecaptured image data and with the measured coverage data; and displaying,by the controller, the correlated coverage impact score value data withthe captured image data and with the measured coverage data at eachlocation.
 8. The method of claim 7, further comprising receiving aplurality of radio frequency (RF) signals from RF transmitters at fixed,known positions in the venue, and locating the mobile data capturedevice at each location by measuring strengths of the plurality of thereceived RF signals.
 9. The method of claim 7, further comprisingrecording and storing the correlated coverage data and the image data ateach location in a database.
 10. The method of claim 7, furthercomprising simultaneously displaying the captured image data and themeasured coverage data at each location.
 11. The method of claim 10,wherein the simultaneous displaying of the captured image data and themeasured coverage data is performed in real time as the mobile datacapture device moves through the venue.
 12. The method of claim 7,further comprising locating at least one recognized object on a map,updating default a value assigned to the at least one recognized objectto a refined value, and determining the coverage impact score value databased on the refined value.